Genetic variants of antioxidant and xenobiotic metabolizing enzymes and their association with prostate cancer: A meta-analysis and functional in silico analysis.

The development and progression of prostate cancer (PCa) depends on complex interactions between genetic, environmental and dietary factors that modulate the carcinogenesis process. Interactions between chemical exposures and genetic polymorphisms in genes encoding xenobiotic metabolizing enzymes (XME), antioxidant enzymes and DNA repair enzymes have been reported as the main drivers of cancer. Thus, a better understanding of the causal risk factors for PCa will provide avenues to identify men at increased risk and will contribute to develop effective detection and prevention methods. We performed a meta-analysis on 17,518 cases and 42,507 controls obtained from 42 studies to determine whether seven SNPs and one CNV pertaining to oxidative stress, xenobiotic detoxification and DNA repair enzymes are associated with the risk of PCa (GPX1 (rs1050450), XRCC1 (rs25487), PON1 (rs662), SOD2 (rs4880), CAT (rs1001179), GSTP1 (rs1695) and CNV GSTM1). A significant increased risk of PCa was found for SOD2 (rs4880) ORGG+GA vs. AA 1.08; 95%CI 1.01-1.15, CAT (rs1001179) ORTT vs. TC+CC 1.39; 95%CI 1.17-1.66, PON1 (rs662) ORCT vs. CC+TT 1.17; 95%CI 1.01-1.35, GSTP1 (rs1695) ORGG vs. GA+AA 1.20; 95%CI 1.05-1.38 and GSTM1 (dual null vs. functional genotype) ORN vs. NN1+NN2 1.34; 95%CI 1.10-1.64. The meta-analysis showed that the CNV GSTM1, and the SNPs GSTP1 (rs1695) and CAT (rs1001179) are strongly associated with a greater risk of PCa and, to a lesser extent, the genetic variants SOD2 (rs4880) and PON1 (rs662). Although several antioxidant enzymes and XME play an important role in the PCa development, other risk factors such as chemical exposures should also be considered to gain insight on PCa risk. The functional in silico analysis showed that the genetic variants studied had no clinical implication regarding malignancy, except for GPX1 (rs1050450) SNP.

Relevance of TMPRSS2, CD163/CD206, and CD33 in clinical severity stratification of COVID-19.

Background: Approximately 13.8% and 6.1% of coronavirus disease 2019 (COVID-19) patients require hospitalization and sometimes intensive care unit (ICU) admission, respectively. There is no biomarker to predict which of these patients will develop an aggressive stage that we could improve their quality of life and healthcare management. Our main goal is to include new markers for the classification of COVID-19 patients. Methods: Two tubes of peripheral blood were collected from a total of 66 (n = 34 mild and n = 32 severe) samples (mean age 52 years). Cytometry analysis was performed using a 15-parameter panel included in the Maxpar® Human Monocyte/Macrophage Phenotyping Panel Kit. Cytometry by time-of-flight mass spectrometry (CyTOF) panel was performed in combination with genetic analysis using TaqMan® probes for ACE2 (rs2285666), MX1 (rs469390), and TMPRSS2 (rs2070788) variants. GemStone™ and OMIQ software were used for cytometry analysis. Results: The frequency of CD163+/CD206- population of transitional monocytes (T-Mo) was decreased in the mild group compared to that of the severe one, while T-Mo CD163-/CD206- were increased in the mild group compared to that of the severe one. In addition, we also found differences in CD11b expression in CD14dim monocytes in the severe group, with decreased levels in the female group (p = 0.0412). When comparing mild and severe disease, we also found that CD45- [p = 0.014; odds ratio (OR) = 0.286, 95% CI 0.104-0.787] and CD14dim/CD33+ (p = 0.014; OR = 0.286, 95% CI 0.104-0.787) monocytes were the best options as biomarkers to discriminate between these patient groups. CD33 was also indicated as a good biomarker for patient stratification by the analysis of GemStone™ software. Among genetic markers, we found that G carriers of TMPRSS2 (rs2070788) have an increased risk (p = 0.02; OR = 3.37, 95% CI 1.18-9.60) of severe COVID-19 compared to those with A/A genotype. This strength is further increased when combined with CD45-, T-Mo CD163+/CD206-, and C14dim/CD33+. Conclusions: Here, we report the interesting role of TMPRSS2, CD45-, CD163/CD206, and CD33 in COVID-19 aggressiveness. This strength is reinforced for aggressiveness biomarkers when TMPRSS2 and CD45-, TMPRSS2 and CD163/CD206, and TMPRSS2 and CD14dim/CD33+ are combined.

Metabolic pathways, alterations in miRNAs expression and effects of genetic polymorphisms of bisphenol a analogues: A systematic review.

Bisphenol A (BPA) is one of the most common endocrine disruptors found in the environment and its harmful health effects in humans and wildlife have been extensively reported One of the main aims of this review was to examine the metabolic pathways of BPA and BPA substitutes and the endocrine disrupting properties of their metabolites. According to the available literature, phase I and phase II metabolic reactions play an important role in the detoxification process of bisphenols (BPs), but their metabolism can also lead to the formation of highly reactive metabolites. The second part of this work addresses the associations between exposure to BPA and its analogues with the alterations in miRNAs expression and the effects of single nucleotide polymorphisms (SNPs). Available scientific evidence shows that BPs can dysregulate the expression of several miRNAs, and in turn, these miRNAs could be considered as epigenetic biomarkers to prevent the development of a variety of BP-mediated diseases. Interestingly, genetic polymorphisms are able to modify the relationship of BPA exposure with the risk of adverse health effects, suggesting that interindividual genetic differences modulate the susceptibility to the effects of environmental contaminants.